How does big data help make large public health decisions? How do we set up the collection, the analysis, and interoperate the data to create infrastructure? Leoson Hoay serves as a Research Analyst and Data Steward at the University of Chicago Urban Labs, working with the Health Lab team to support the creation of data-driven solutions to public health problems. Prior to joining the Urban Labs, he had worked in various fields spanning data engineering, mental health counseling, and environmental remediation with organizations in the US, Singapore, and Australia. Leoson received his MA in Computational Social Science from the University of Chicago, and his undergraduate degree in Psychology from the National University of Singapore. He is currently pursuing an MS in Computer Science at the Georgia Institute of Technology.

In this episode we discuss many big questions invovling the use of big data to solve large problems. We dive into two projects Leoson has contributed to and generally discuss what big data means in the context of health decisions. Check it out!